Machine Learning Modeling for IoUT Networks
Internet of Underwater Things
(Sprache: Englisch)
This book discusses how machine learning and the Internet of Things (IoT) are playing a part in smart control of underwater environments, known as Internet of Underwater Things (IoUT). The authors first present seawater's key physical variables and go on to...
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Klappentext zu „Machine Learning Modeling for IoUT Networks “
This book discusses how machine learning and the Internet of Things (IoT) are playing a part in smart control of underwater environments, known as Internet of Underwater Things (IoUT). The authors first present seawater's key physical variables and go on to discuss opportunistic transmission, localization and positioning, machine learning modeling for underwater communication, and ongoing challenges in the field. In addition, the authors present applications of machine learning techniques for opportunistic communication and underwater localization. They also discuss the current challenges of machine learning modeling of underwater communication from two communication engineering and data science perspectives.Inhaltsverzeichnis zu „Machine Learning Modeling for IoUT Networks “
Introduction.- Seawater's Key Physical Variables.- Opportunistic Transmission.- Localization and Positioning.- ML Modeling for Underwater Communication.- Open Challenges.- Conclusion.Autoren-Porträt von Ahmad A. Aziz El-Banna, Kaishun Wu
Ahmad A. Aziz El-Banna received his Master's degree in 2011 from Benha University and his Ph.D in 2014 from Egypt-Japan University of Science & Technology. Since June 2018, he has been a postdoctoral fellow at Shenzhen University, China. He also holds the position of an assistant professor at Benha University, Egypt. He served as a visiting researcher at Osaka University at Japan (2013-2014). His research interests include cooperative networking, MIMO, space-time coding, IoT, machine learning, and underwater communication.
Bibliographische Angaben
- Autoren: Ahmad A. Aziz El-Banna , Kaishun Wu
- 2021, 1st ed. 2021, XII, 63 Seiten, 24 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3030685667
- ISBN-13: 9783030685669
Sprache:
Englisch
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